Since the early 1980s the aim of knowledge management researchers and practitioners has been to develop technologies and systems to codify and share explicit knowledge efficiently through electronic means. With the growing appreciation of the importance of tacit knowledge [1], we have a new problem: how to facilitate other forms of systematic organisational learning and knowledge exchange where knowledge cannot be codified.

In this article we take a further step by looking at the problem of analysing and managing complex knowledge in organisations that have multiple specialised knowledge communities. Here the challenge for knowledge management is not only to make knowledge available in repositories for dissemination across the firm. More broadly, if firms are to deliver value-creating goods and services, they now need to be able to combine and integrate specialised forms of knowledge from different communities each with their own professional languages, traditions and objectives. In this paper we present and develop a framework which elaborates on this problem and offers some guidance about how it might be tackled.

Three Approaches to Knowledge Integration across Boundaries

There is a trend towards increasing specialisation both in academia and practice. In science we have a proliferation of disciplines and sub-disciplines. In organisations, technologies and specialised knowledge domains become more specialised. For example, the first cell phones required 5 distinct technologies to be combined, while third-generation cell phones incorporated 14 distinct sub-technologies [2].

Knowledge-intensive firms consist of multiple communities with specialised technologies and knowledge domains. A high degree of shared knowledge within specialised knowledge communities facilitates interaction and exchange. At the same time there are boundaries between different knowledge communities - e.g. between design, manufacturing and sales - with a lower degree of shared knowledge. Sharing and integrating knowledge across these boundaries is vital for firms to coordinate their activities and deliver their products and services.

In this context, knowledge management is not only making explicit information available in repositories across the firm, but more broadly to facilitate organisations’ ability to share and integrate knowledge efficiently across domains. This is especially a challenge with novel knowledge and high interdependencies between knowledge domains.

Carlile [3] [4] developed a useful framework for managing knowledge across boundaries. There are three approaches or levels for managing increasingly complex knowledge and interdependencies between knowledge communities.

The first - a syntactic approach - conceives of knowledge transfer as the process of sending and receiving messages, and is useful in conditions of low novelty and highly shared context. The second - a semantic approach - builds on the first, but also recognise the importance of interpretation and meaning that can vary across knowledge communities. The third - a pragmatic approach - incorporates the first two, and recognises that new knowledge in one knowledge domain may have costs in other domains, requiring joint problem-solving and negotiations of interests and trade-offs.

Syntactic Approach: Shared Syntax as a Basis for Information Processing

Models and systems for knowledge sharing in organisations are often informed by a syntactic model of communication - or a conduit model, inspired by the communications theory of Shannon and Weaver [5]. This portrays communication as a process of sending and receiving messages through a transmission channel with limited channel capacity. Noise can distort messages between sender and recipient, and this can be alleviated by improving the channel capacity (for example going from e-mail to telephone or face-to-face), or by refining procedures for coding and decoding messages (for example Morse code).

In this approach, accurate and reliable communication can be secured by establishing a shared and stable syntax for coding and decoding of messages. Web pages must follow the protocol of Hypertext Markup Language for a Web browser to be able to read and display it. During military operations, to achieve communication efficiency and reduce risk of errors, units co-ordinate tactical manoeuvres by communicating through messages from a pre-defined set of codes and signals.

In a scientific community, the stronger and more developed a shared perspective is (regarding ontology, theories, methods, and empirical phenomena of interest), the more useful is a syntactic approach. ‘As theories, puzzles, measures and accepted results are clarified and institutionalised within the community, the more likely it is that messages can be thought of as selections from a predefined set’ [6]. To understand a journal article, for example on breakthrough neuroscientific discoveries, one requires a high level of training in that field, having acquired an overview of existing research, proper methods and terminology. The lay public does not have the same vocabulary and fore-knowledge to decode messages in research articles.

These examples show how a common syntax, definition of concepts and defined methodologies for constructing knowledge are required for effective knowledge transfer. The syntactic perspective conceives the process as information processing, with coding and decoding of messages. However, the syntactic approach has one weakness; it treats the meaning of a message as unproblematic. Encoding and decoding is seen as selection of messages from a pre-selected set. The problem of human meaning is not considered. A semantic approach acknowledges interpretation as a central element in communication and knowledge integration.

Semantic Approach: Interpreting Novel Knowledge

‘A semantic approach recognizes that even if a common syntax or knowledge is present, interpretations are often different which make communication and collaboration difficult.’ [7]

Within scientific communities, one uses definition of concepts and clearly specified methodologies to reduce risks of differing interpretations. Fellow researchers can still arrive at very different interpretations and conclusions when reading a research paper, based on their interests, values and previous related knowledge.

Dougherty [8] provided an example from a product development process, where a cross-disciplinary team had agreed on making the product ‘market-oriented’. However the concept of being market-oriented was interpreted in very different ways. For product designers this meant incorporating increased functionality in the product; production managers laid emphasis on manufacturing a reliable product; whereas sales personnel wanted to be able to tailor the product to each customer’s wishes. Sometimes interpretation is so automatic we are not aware that interpretation is involved in decoding a message. A false consensus was created, based on the belief that each knowledge community took its interpretation of ‘market-oriented’ as natural and self-evident, and thus shared with other communities.

Members of different specialised knowledge communities can be said to reside in different ‘thought worlds’ [8]. Central ideas in one community may be considered uninteresting or irrelevant in another. Collaboration can be difficult across disciplines, because individuals give different meanings to the same concept. Researchers in cognate areas may use the same terms, but define them differently (Kroeber and Kluckhohn [9] found over 150 definitions of the concept ‘culture’). Vice versa, researchers may address the same empirical phenomena with different theories and concepts.

Organisations thus need tools and mechanisms to reconcile discrepancies in meaning and develop shared understanding of knowledge across boundaries. Co-location of personnel, cross-functional teams [10], and job rotation between locations and functions [11] are some organisational mechanisms to facilitate shared understanding. Carlile [3] also points to the important role of boundary objects such as visualisation tools, drawings, spreadsheets to provide a shared locus for collaborative inquiry - e.g. in a cross-functional team - to examine each other’s understandings and interpretations of shared knowledge. Various knowledge communities have dominant forms of representation that capture important aspects of knowledge in their domains, but render other communities’ concerns invisible. Carlile reports on a product development process, where two-dimensional engineering design drawings did not contain nor visualise critical dependencies for manufacturing on tolerances between components; nor did they address how to achieve a manufacturing-friendly design. On the other hand, 3D manufacturing engineering drawings worked well as a boundary object between design and engineering managers, because they supported informed discussion of critical issues as seen by both communities.

The Pragmatic Approach: Negotiating and Transforming Knowledge

The semantic approach goes further than the syntactic approach in framing challenges for managing knowledge between different knowledge communities. Being aware of possible differences in interpretation and meaning, and using tools and mechanisms to develop shared understanding is an important step.

However, the semantic perspective does not incorporate the fact that interdependencies between knowledge communities also involve vested interests in certain technologies, solutions and knowledge from one’s own knowledge domain. Knowledge within a community is geared towards solving problems or making things work within that community’s knowledge domain. A ‘hard-won outcome’ [3] means that the community has invested material and mental effort in developing solutions. These solutions may have costs and negatively affect other knowledge domains.

The pragmatic dimension of knowledge integration resonates with the somewhat too simplistic equation ‘knowledge is power’. What for one group or knowledge community constitutes a big leap forward in terms of knowledge or a radical innovation, may incur costs for another community.

Likewise, knowledge stored within corporate databases or information systems is not neutral. A so-called best practice can be challenged or controversial. A particular approach or procedure may shift the balance between professions. A new best practice from one unit may render the practices of other units obsolete.

Here we do not focus on knowledge sharing between similar, independent units. We focus, rather, on the knowledge sharing and integration between interdependent but different knowledge communities. On the boundary between knowledge communities one needs not only to uncover different interpretations and develop shared understanding. In order to develop workable solutions, one needs to engage in joint problem solving and developing new knowledge, as well as negotiating interests and trade-offs as technologies from various domains influence other domains.

Carlile [4] describes how an engine engineering community of a car company had developed a larger, more powerful, yet energy-efficient engine in conjunction with a new car model under development. It was only later recognised that this necessitated a higher bonnet to house the new engine. This negatively affected the lines of the bonnet, which was the responsibility of the styling group. There is a high degree of dependency between various knowledge communities designing a car. New knowledge in one sub-system (engine) affects the boundary conditions that other design groups have to work within (height of the hood given the size of the engine, types of suspension and brakes, given the weight of the car, etc.). The traditional boundary object of a clay model of the car was, in this case, inadequate to discover this interdependency. This is not simply a situation of choice under uncertainty among groups that vary in their preferences. The novelty of knowledge is central, because the novelty of the engine solution from one community may not be recognised by another. This failure to discover interdependencies early in the process led to redesign, a reduced collaborative climate, additional costs and delays in launching the new car model.

Again, boundary objects that can represent knowledge from various communities and facilitate understanding and interaction between communities are important. For infrastructure investments that affect landscape and the natural environment, Geographical Information Systems (GIS) can provide boundary objects that represent complex relationships in a way that facilitates an informed discussion on costs, benefits and trade-offs for various stakeholders. In a planning project for a wind farm in western Norway, there were several important interdependencies with this relatively new technology, accompanied by significant uncertainty about the environmental impact. GIS was used to visualise the effects of the planned wind farm - areas containing important bird reserves, areas that would be within sight of the wind farms, areas and levels of sound pollution for residents, areas of cultural significance, major tourist shipping lanes etc. GIS proved to be an efficient tool for visualising the effects, thereby developing the means to a shared understanding of the environmental impact of the project among stakeholders such as local inhabitants, wildlife conservationists, government. Furthermore it consequently permitted informed discussion on actual trade-offs. Relying solely on verbal or written arguments would have been less likely to reveal the actual impact of, and interdependencies existing within the project. Moreover the risk of parties failing to convey their particular priorities and concerns to other stakeholders would have been far higher.

Summary

Knowledge sharing in organisations is traditionally conceived as the process of sending and receiving messages. This reflects the first approach in this framework. In this perspective, effective knowledge transfer hinges on shared syntax and language for individuals to be able to decode messages. This perspective is suitable for knowledge sharing within specialised knowledge communities where there is a high level of shared knowledge. However, the perspective is somewhat limited for managing knowledge sharing and knowledge integration between communities with specialisation in different knowledge domains. With a lower degree of shared language one needs more elaborate mechanisms in order to cope.

The second approach emphasises differences in interpretation and meaning. Different knowledge communities have their own language, important issues and methodologies. With interdependencies, where novel knowledge from multiple communities is to be integrated, organisations need effective mechanisms for reconciling differences and developing shared understanding.

The third approach - a pragmatic approach - points out that new knowledge in one community can have negative impacts on other communities. Collaboration on the boundaries between knowledge communities is thus not only about joint knowledge production, but also about identifying interdependencies and trade-offs, and negotiating interests.

This framework, with three approaches for managing interdependent knowledge on the boundaries between knowledge communities, identifies boundary objects as important tools for knowledge integration. Boundary objects such as documents, Geographic Information Systems, design drawings, and Excel sheets can facilitate development of shared understanding, exploring the perspectives of others, and uncovering interdependencies and interests. The fast pace of technological development in information and communication technologies has opened up many new avenues for technology-mediated interaction. Boland and Tenkasi [12] point out that ‘Any design of an electronic communication system implies a model of human communication and human cognition’. Often the model underlying a KM system is implicit and not much reflected upon. Many of the early developments in knowledge management were grounded on a somewhat limited model of communication as information processing, as sending and receiving of messages. It is our hope that future developments in ICT-mediated communication systems will be informed by richer and more nuanced models of human cognition together with the organisational dynamics of sharing knowledge between specialised communities in organisations.